Generating document content by data analysis

ABSTRACT

Systems and methods for generating document content using data analysis. For example, a system may store data representing one or more documents, where a document is associated with a type of user and fields. The system may send the data representing the document to an electronic device. Additionally, the system may receive, from the electronic device, data representing information input into the document. Using the information, the system may select various fields for the document and send, to the electronic device, data representing the fields. Furthermore, the system may analyze the information to determine a score associated with the document. If the score does not satisfy a threshold score, the system may continue to select fields using the information and send, to the electronic device, data representing the fields. However, if the score satisfies the threshold score, the system may determine that the document is complete.

BACKGROUND

In order to receive information about a user, such as a patient beingexamined, the information may be input into a document. For example, thedocument may ask a series of questions in order to obtain theinformation, such as the user's name, age, weight, symptoms, testresults, and so forth. Once the information is input into the document,the information may be analyzed by another user, such as a doctor, inorder to diagnosis the patient. However, different patients may havedifferent diagnoses and as such, a system may be required to storedocuments that include questions related to multiple diagnoses. This cancause problems, as computer code must be generated for each of thedocuments, which can require computing resources. Additionally, storingthe data for each of the documents can require a lot of memory.

Furthermore, information may be input into a document that is notrelevant to an actual diagnosis of a user. For example, if the user hasheart disease, the document will include questions related to heartdisease as well as other diagnoses, such as cancer or diabetes. Thisadditional information may make it more difficult to diagnose the user,since it is not actually relevant to the actual diagnosis.

BRIEF DESCRIPTION OF THE DRAWINGS

The detailed description is set forth below with reference to theaccompanying figures. In the figures, the left-most digit(s) of areference number identifies the figure in which the reference numberfirst appears. The use of the same reference numbers in differentfigures indicates similar or identical items. The systems depicted inthe accompanying figures are not to scale and components within thefigures may be depicted not to scale with each other.

FIG. 1 illustrates a schematic diagram of an example environment forgenerating document content by data analysis, according to variousexamples of the present disclosure.

FIG. 2 illustrates a block diagram of an example electronic device thatcan generate document content by data analysis, according to variousexamples of the present disclosure.

FIG. 3 illustrates a diagram of a first example of updating a documentwith fields as information is being input into the document, accordingto various examples of the present disclosure.

FIG. 4 illustrates a diagram of a second example of updating a documentwith fields as information is being input into the document, accordingto various examples of the present disclosure.

FIG. 5 illustrates a diagram of a third example of updating a documentwith fields as information is being input into the document, accordingto various examples of the present disclosure.

FIG. 6 illustrates a diagram of an example structure that may beutilized to select fields for a document, according to various examplesof the present disclosure.

FIGS. 7A-7B illustrate a flow diagram of an example process for updatingfields of a document as information is being input into the document,according to various examples of the present disclosure.

FIG. 8 illustrates a flow diagram of an example process for updatingfields of a document, according to various examples of the presentdisclosure.

FIG. 9 illustrates a flow diagram of an example process for using scoresto determine whether a document is complete, according to variousexamples of the present disclosure.

FIG. 10 illustrates a flow diagram of an example process for using aperiod of time to select at least one field for a document, according tovarious examples of the present disclosure.

FIG. 11 illustrates a flow diagram of an example process for anelectronic device updating fields of a document, according to variousexamples of the present disclosure.

DETAILED DESCRIPTION

The present application is directed to systems and methods forgenerating document content using data analysis. For example, an entity,such as a user, group, business, corporation, medical facility, and/orso forth, can use documents to obtain information. In some examples, adocument can include a number of fields (e.g., properties, elements,etc.), where a field can be updated with information that is relevant tothe field. For example, an employee at a medical facility, such as adoctor or nurse, can use a document to determine information about apatient. The document can include a number of fields, where the employeeinputs respective information into one or more of the fields. Forexample, the fields can include a first field associated with a name ofthe patient, a second field associated with an age of the patient, athird field associated with a weight of the patient, a fourth fieldassociated with symptoms the patient is having, a fifth field associatedwith results of tests performed on the patient, and/or so forth. Theemployee can then input the information that is relevant to the fieldsinto the document. Using the information, the employee and/or anotheremployee can diagnose the patient.

In some examples, a system can store data representing variousdocuments, where an individual document is associated with a type ofuser and/or one or more fields. For example, the system can store datarepresenting a first document that doctors use to obtain informationrelated to patients, where the first document is associated with firstfields. The system can further store data representing a second documentthat nurses use to obtain information related to patients, where thesecond document is associated with second fields. Although these arejust a couple of examples of documents that are specific to types ofusers in the medical industry, in other examples, the system can storedocuments that are specific to types of users in other industries. Forexamples, in the legal industry, the system can store data representingdocuments that associated with partner attorneys, associate attorneys,paralegals, and/or so forth.

In some examples, the system can further store data representing rulesfor selecting fields for a document. The rules can indicaterelationships between fields, such that a field is selected based atleast in part on information that is input into one or more otherfields. For a first example, a first field can represent a question withat least two responses, where a first response is related to a secondfield and a second response is related to a third field. As such, a rulecan indicate that (1) when the first response is selected for the firstfield, the second field is selected for the document and (2) when thesecond response is selected for the first field, the third field isselected for the document. For a second example, a first field canrepresent a question that is requesting information that includes anumerical value. A first range of values for the numerical value can beinclude a relationship to a second field and a second range of valuesfor the numerical value can be related to a third field. As such, a rulecan indicate that (1) when a numerical value that is included in thefirst range of values is input into the first field, the second field isselected for the document and (2) when a numerical value that isincluded in the second range of values is input into the first field,the third field is selected for the document. While these are just acouple of examples of rules, the system can store data representingother types of rules, which are described below.

The system can provide the documents to users so that the users can usethe documents to obtain information. For example, the system canreceive, from an electronic device, data representing a request for adocument. In some examples, the data can further represent a type ofuser that is requesting the document. Using the data, the system canselect a document for the user. For example, if the data represents thetype of user, the system can select the document that is associated withthe type of user. The system can then send, to the electronic device,data representing the selected document. In some examples, the documentincludes one or more initial fields which the user can use to inputinitial information. For example, if the user is a nurse obtaininginformation about a patient, the one or more initial fields can berelated to questions asking about the patient's name, age, weight,and/or initial diagnosis.

As the user inputs the information into the fields, the system canreceive, from the electronic device, data representing the information.The system can then analyze the information using the rules in order toselect additional fields for the document. For a first example, aninitial field can represent a question that includes a number ofresponses, where a rule indicates that (1) when a first response isselected for the initial field, a first additional field is selected forthe document and (2) when a second response is selected for the initialfield, a second additional field is selected for the document. Based atleast in part on the analysis, the system can determine that theinformation represents the first response. The system can use the ruleassociated with the initial field to select the first additional field.For a second example, an initial field can represent a question that isrequesting information that includes a numerical value, wherein a rulecan indicate that (1) when the numerical value is included in a firstrange of values, the a first additional field is selected for thedocument and (2) when the numerical value is included in a second rangeof values, a second additional field is selected for the document. Basedat least in part on the analysis, the system can determine that theinformation represents a numerical value that is included in the firstrange of values. The system can the use the rule associated with theinitial field to select the first additional field.

The system can send, to the electronic device, data representing the oneor more additional fields. In some examples, the data can furtherrepresent a command to populate the document with the one or moreadditional fields. The system can then continue to receive, from theelectronic device, data representing information that is input into thedocument (e.g., input into the one or more additional fields). Using thedata and/or the rules, the system can continue to select one or moreadditional fields, using the techniques above. Additionally, the systemcan continue to send, to the electronic device, data representing theone or more additional fields and/or a command to populate the documentwith the one or more additional fields.

In some examples, while receiving the data representing the informationinput into the document, the system can analyze the information todetermine a correlation score associated with the information. Thesystem can then determine if the correlation score satisfies (e.g., isequal to or exceeds) a threshold score. Based at least in part ondetermining that the correlation score satisfies the threshold score,the system can refrain from selecting and/or providing additional fieldsfor the document and/or the system can determine that document iscomplete. In some examples, the system determines the correlation scoreeach time the system receives additional information that is input intoa field of the document. In some examples, the system determines thecorrelation score when the system receives additional information thatis input into two or more fields of the document.

For example, if the document is associated with diagnosing a patient,the system can analyze first information to determine a firstcorrelation score indicating how closely the first information relatesto standard information (e.g., symptoms and/or expected test results)associated with a diagnosis. Based at least in part on the firstcorrelation score satisfying a threshold score, the system can refrainfrom selecting and/or providing additional fields for the documentand/or the system can determine that document is complete. Additionally,in some examples, the system can determine the diagnosis for thepatient. However, based at least in part on determining that the firstcorrelation score does not satisfy (e.g., is less than) the thresholdscore, the system can select at least one additional field for thedocument. The system can then send, to the electronic device, datarepresenting the at least one additional field and/or a command topopulate the document with the at least one additional field.

The system can then receive, from the electronic device, secondinformation related to the at least one additional field. Based at leastin part on receiving the second information, the system can determine asecond correlation score indicating how closely the first informationand/or the second information relate to the standard informationassociated with the diagnosis. Based at least in part on the secondcorrelation score satisfying the threshold score, the system can refrainfrom selecting and/or providing additional fields for the documentand/or the system can determine that document is complete. Additionally,in some examples, the system can determine the diagnosis for thepatient. However, based at least in part on determining that the secondcorrelation score does not satisfy the threshold score, the system cancontinue to select at least one additional field for the document,determine at least one additional correlation score for the informationinput into the document, and determine whether the at least oneadditional correlation score satisfies the threshold score.

In some examples, when diagnosing a patient, the system can use theinformation to determine correlation score(s) associated with one ormore other diagnoses. The system can then determine whether thecorrelation score(s) satisfy the threshold score. Based at least in parton determining that a correlation score associated with a diagnosisexceeds the threshold score, the system can diagnose the patient.Additionally, in some examples, the system can select additional fieldsthat are associated with the diagnosis. The system can then send, to theelectronic device, data representing the additional fields. Based atleast in part on the additional fields, the system can then receiveinformation that is related to the determined diagnosis.

In some examples, such as when time is a factor for completing thedocument, the system can determine a period of time associated with thedocument. For example, the system can receive, from the electronicdevice, data representing the period of time. The system can then usethe period for time when selecting the fields for the document. For afirst example, the system can select between first fields for a firstperiod of time and second fields for a second, different period of time.In such an example, if the first period of time is less than the secondperiod of time, at least some of the first fields can be related toquestions with selectable responses, such that a user completing thedocument can quickly select a respective response for the first fields.Additionally, the second fields can be related to questions in which theuser manually inputs the responses, which can take longer for the userto complete. However, the responses for the second fields can includemore information.

For a second example, the system can use the period of time to determinea number of fields for the document. The system can then select thefields for the document based on the number of fields. For instance, ifthe number of fields is below a threshold number of fields (e.g., twofields, five fields, ten fields, etc.), then the system may selectfields that request information associated with an initial diagnosis.However, if the number of fields exceeds the threshold number of fields,then the system may select fields that request information associatedwith the initial diagnosis as well as other similar diagnosis.

In some examples, the system can utilize previous reports (e.g.,records) in order to select fields for the document and/or update theselected fields for the document. For a first example, and if thedocument is associated with a patient, the system can analyzeinformation included in at least one previous report associated with thepatient to determine a diagnosis (e.g., using correlation scores, usinginformation indicating the diagnosis, etc.) for the patient. The systemcan then use the rules to select fields that are related to thediagnosis. For a second example, and again if the document is associatedwith a patient, the system can analyze information included in at leastone previous report to update at least one field of the document suchthat the at least one field is tailored towards the patient. Forinstance, if the field is related to a question such as “How much do youweigh?”, and the information included in the at least one previousreport indicates that the patient previously weighed 120 pounds, thensystem can update the question to “Do you still weigh 120 pounds?”.

For a third example, the system can store data representing a firstreport for a first patient and data representing a second report for asecond patient, where the second report indicates a diagnosis for thesecond patient. The system can then analyze the first report withrespect to the second report to identify at least one similarity betweenthe first report and the second report. For instance, the at least onesimilarity can include that the first report and the second report eachrepresent information indicating one or more common symptoms. Based atleast in part on the at least one similarity, the system can diagnosethe first patient (e.g., the first patient has the same health problemas the second patient). The system can then use the diagnosis as aninitial diagnosis the next time that a document is being utilized toobtain information associated with the first patient.

In some examples, the system can determine that the document iscomplete. For a first example, the system can determine that acorrelation score for the document satisfies a threshold score. For asecond example, the system can receive, from the electronic device, dataindicating that the document is complete. Still, for a third example,the system can determine that the period of time has elapsed. In eitherexample, the system can generate a report related to the document. Insome examples, the report can include data that represents the fields ofthe document and/or the information that was input into the fields ofthe document. The system can then store the report in one or moredatabases. Additionally, in some examples, the system can send the datarepresenting the report to the electronic device and/or an additionalelectronic device.

In some examples, the system generates the report to include all of thefields and information that are included within the document. In someexamples, the system generates the report to include a portion of thefields and information that are included within the document. For afirst example, if the system determines a diagnosis using the document,the system may generate the report to include the fields and informationthat are included within the document and relevant to the diagnosis. Fora second example, if the document includes sensitive information (e.g.,personal information, mental health information, whether the user hascertain medical diseases, etc.), then the system may generate the reportto include the fields and information included within the document thatare not related to the sensitive information.

In some examples, a user may select the fields and information that areincluded within the report. For instance, the system may receive datarepresenting which fields and/or information from the document toinclude within the report. The system may then generate the report toinclude the fields and/or information indicated by the data. In someexamples, the system may generate the report to include all of thefields and information from the document, but may “hide” some of thefields and/or information when sending the report to a user. Forexample, if a user is not authorized to view sensitive informationincluded within the report, the system may cause the sensitiveinformation to no longer be included within the report when sending thereport to the user.

In some examples, the system may generate the report such that thefields and information are displayed using a tabular format. In someexamples, the system may generate the report using other types offormats. In some examples, when viewing the report, a user may selectthe fields and information for which the user wishes to view. The systemmay then cause the report to display the selected fields and informationwhile “hiding” other fields and information that were not selected bythe user. As such, the user may utilize the report to easily findinformation that is relevant to how the user is using the report. Still,in some examples, a user may use the report to generate new rules thatcan later be used by the system to select fields for documents.

As described herein, a document can include a form (e.g., open endedform, close ended form, mixed open ended and close ended form, etc.), aspreadsheet, a report, a chart, a schedule, a transcript, a notice, anote, a file, an agreement, a book, and/or any other type of document. Adocument can be associated with one or more fields for inputtinginformation. For a first example, a field can represent a question withone or more responses (e.g., information) for selection. For a secondexample, a field can represent a question and an interface element forinputting a response (e.g., information). Additionally, information caninclude one or more words, one or more numerical values, one or moresymbols, one or more selectable responses, and/or any other type ofinformation that can be input into a document.

In some examples, a document may be utilized to obtain informationassociated with a patient. For example, one or more of fields of thedocument may be associated with receiving initial information related tothe patient (e.g., age, sex, weight, etc.). Additionally, one or morefields of the document may be associated with receiving informationrelated to symptom(s) being experienced by the patient. Furthermore, oneor more fields of the document may be associated with receivinginformation related to test(s) performed on the patient. In suchexamples, the information input into the document can be used diagnosethe patient. For example, the remote system may analyze the information(e.g., the initial information, the symptom(s), the test result(s),etc.) to diagnose the patient.

In some examples, by performing the processes and/or techniquesdescribed above to select fields for populating a document, the systemis not required to store data representing multiple documents. Rather,the system can store data representing a document and then select fieldsfor populating the document as information is received from anelectronic device. This can cause the system to store less data, whichcan improve the system. Additionally, the system is capable of providinga document that is more relevant to a diagnosis, since the fields (e.g.,questions) included in the document are selected and/or updated based atleast in part on information that is being input into the document. Assuch, the information input into the document and/or the data receivedby the system can be more relevant to the actual diagnosis.

Although the above description includes the system analyzing informationinput into a document to select fields and/or determine whether thedocument is complete, in some examples, one or more electronic devicescan analyze the information input into the document to select fieldsand/or determine whether the document is complete.

FIG. 1 illustrates a schematic diagram of an example environment 100 forgenerating document content by data analysis, according to variousexamples of the present disclosure. The environment 100 can include aremote system 102 and an electronic device 104 that is inputtinginformation into a document 106 over the course of a period of time, forexample. In some examples, the remote system 102 represents a systemthat generates and/or acquires data associated with one or moredocuments and stores that data. The remote system 102 can furtherrepresent a system that generates document content using the receiveddata. In some examples, the electronic device 104 can receive inputsfrom users and, based at least in part on the inputs, generate inputdata. The input data can indicate information that is input into thedocument 106.

The electronic device 104 can communicate with the remote system 102 viaone or more networks 108. The communication can include sending and/orreceiving of data 110 associated with the document 106. In someexamples, the data 110 can represent the information that is input intothe document 106 (e.g., the input data generated by the electronicdevice 104). For example, the remote system 102 can receive the data 110when the electronic device 104 receives input indicating information toinput into the document 106. In some examples, the data 110 canrepresent fields 112(1)-(5) to be populate the document 106.

The remote system 102 can include one or more components, such as, forexample, processor(s) 114, network interface(s) 116, and memory 118. Thememory 118 can include one or more components, such as, for example, adocument component 120, a rules component 122, a field component 124, ascore component 126, a report component 128, and one or more databases130. The one or more databases 130 can be configured to store datareceived by the remote system 102. For example, the one or more datadatabases 130 can be configured to receive and store the data 110received from the electronic device 104. In some examples, the one ormore databases 130, and/or one or more other components of the remotesystem 102, can be configured to format the data for storage in the oneor more databases 130 such that the data is associated with anidentifier of the document 106. For example, the data 110 associatedwith the document 106 can be received from the electronic device 104.The electronic device 104 can send the data 110 in the same or differingformats and/or can send the data 110 with differing identificationformats. The one or more databases 130 and/or other components of theremote system 102 can be configured to associate the data 110 such thatthe data 110 is associated with the proper document 106 in the one ormore databases 130.

The document component 120 can be configured to generate documents andthen store document data 132 representing the documents. In someexamples, the document component 120 generates the documents using data110 received from one or more electronic devices, such as the electronicdevice 104. For example, the data 110 can indicate one or more fields toinclude in the documents. In some examples, one or more of the documentscan be associated with a type of user. For example, the remote system102 can store document data 132 representing a first document thatdoctors use to obtain information related to patients. The remote system102 can further store document data 132 representing a second documentthat nurses use to obtain information related to patients. Althoughthese are just a couple of examples of documents that are specific totypes of users in the medical industry, in other examples, the remotesystem 102 can store document data 132 representing documents that arespecific to types of users in other industries. For examples, in thelegal industry, the remote system 102 can store document data 132representing documents that associated with partner attorneys, associateattorneys, paralegals, and/or so forth.

In some examples, the document component 120 can associate document data132 representing a document with field data 134 representing one or morefields that can be included within the document. For example, the remotesystem 102 can associate the document data 132 representing the firstdocument that doctors use to obtain information related to patients withfield data 134 representing one or more first fields. As discussedherein, the one or more first fields can be initially included withinthe first document and/or added to the first document while the doctorsare inputting information into the first document. Additionally, theremote system 102 can associate document data 132 representing thesecond document that nurses use to obtain information related topatients with field data representing one or more second fields. Asdiscussed herein, the one or more second fields can be initiallyincluded within the second document and/or added to the second documentwhile the nurses are inputting information into the second document.

The rules component 122 can be configured to generate rules data 136representing one or more rules for selecting fields for a document. Insome examples, the rules component 122 generates the rules data 136based at least in part on data 110 received from one or more electronicdevices, such as the electronic device 104. For example, the data 110can represent a rule, and the rules component 122 can store the data 110as rules data 136 in the memory 118.

The rules can indicate relationships between fields, which the remotesystem 102 utilizes in order to select fields for a document. For afirst example, a first field can represent a question with at least tworesponses, where a first response is related to a second field and asecond response is related to a third field. As such, a rule canindicate that (1) when the first response is selected for the firstfield, the second field is selected for the document and (2) when thesecond response is selected for the first field, the third field isselected for the document. For a second example, a first field canrepresent a question that is requesting information that includes anumerical value. A first range of values for the numerical value canrelate to a second field and a second range of values for the numericalvalue can related to a third field. As such, a rule can indicate that(1) when a numerical value that is included in the first range of valuesis input into the first field, the second field is selected for thedocument and (2) when a numerical value that is included in the secondrange of values is input into the first field, the third field isselected for the document.

In some examples, the rules can structure the fields similar to a “treestructure”. For example, a first level (e.g., first step) of the treestructure can include one or more first fields. At least one of the oneor more first fields can include one or more “branches” that connect toone or more second fields located on a second level (e.g., a secondstep) of the tree structure. Additionally, at least one of the secondfields can include one or more “branches” that connect to one or morethird fields located on a third level (e.g., a third step) of the treestructure. This can continue for one or more additional steps throughoutthe tree structure. In some examples, a “branch” that connects twofields together can represent an association (e.g., a rule) between thetwo fields. An example tree structure is described below with regard toFIG. 6.

In the example of FIG. 1, the remote system 102 can receive, from theelectronic device 104, data 110 representing a request for the document106. In some examples, the data 110 can indicate an identifierassociated with the document 106. The identifier can include, but is notlimited to, a name, a numerical identifier, an alphabetic identifier, amixed numerical and alphabetic number, and/or any other type ofidentifier that can be used to identify the document 106. In someexamples, the data 110 can further indicate a type of user that isrequesting the document 106. The document component 120 can then utilizethe data 110 to select the document 106. For a first example, if thedata 110 indicates the identifier of the document 106, the documentcomponent 120 can match the identifier of the document 106 to documentdata 132 that also indicates the identifier of the document 106. Basedon the match, the document component 120 can identify the document 106.For a second example, if the data 110 indicates the type of user, thedocument component 120 can match the type of user to document data 132that also indicates the type of user. Based on the match, the documentcomponent 120 can identify the document 106. In either example, theremote system 102 can then send, to the electronic device 104, thedocument data 132 representing the document 106.

The electronic device 104 can receive the document data 104 and displaythe document 106 to the user. In the example of FIG. 1, the document 106at time T1 (e.g., the top-left illustration of the document 106)includes a first field 112(1). In some examples, such as when thedocument 106 is for obtaining information associated with a patient, thefirst field 112(1) can represent a question associated with an initialdiagnosis of the patient (e.g., “What is your initial diagnosis?). Insuch an example, the electronic device 104 can receive an inputindicating the initial diagnosis (e.g., “Heart Disease”). The electronicdevice 104 can then input first information representing the initialdiagnosis into the document 106 (e.g., into the first field 112(1)).Additionally, the electronic device 104 can send, to the remote system102, data 110 representing the first information.

The remote system 102 can receive, from the electronic device 104, data110 representing the first information input into the first field 112(1)(e.g., the initial diagnosis). The field component 124 can then beconfigured to select one or more additional fields to add to thedocument 106. To select the one or more additional fields, the fieldcomponent 124 can analyze the first information using the rules data136. For example, and continuing with the example above where thedocument 106 is for obtaining information associated with the patient, arule can indicate that at least a second field 112(2) and a third field112(3) are related the first field 112(1) when the first informationinput into the first field 112(1) indicates the initial diagnosis (e.g.,Heart Disease). As such, and based at least in part on the firstinformation and the rule, the field component 124 can select the secondfield 112(2) and the third field 112(3) for the document 106. The remotesystem 102 can then send, to the electronic device 104, field data 134representing the second field 112(2) and the third field 112(3).Additionally, the remote system 102 can send, to the electronic device104, additional data that includes a command to populate the document106 with the second field 112(2) and the third field 112(3).

The electronic device 104 can receive the field data 134 and/or theadditional data from the remote system 102. In the example of FIG. 1, attime T2 (e.g., the top-right illustration of the document 106), theelectronic device 104 can then populate the document 106 with the secondfield 112(2) and the third field 112(3). In some examples, each of thesecond field 112(2) and the third field 112(3) can represent questionsrelated to the first information input into the first field 112(1). Forexample, when the first information represents the initial diagnosis,each of the second field 112(2) and the third field 112(3) can representquestions related to obtaining information that can be used to determinewhether the initial diagnosis is accurate. For examples, if the initialdiagnosis includes “Heart Disease”, then the second field 112(2) canrepresent a question such as “Have you had any chest pains?” and thethird field 112(3) can represent a question such as “Have you feltnausea?”. In other words, the second field 112(2) and the third field112(3) are related to symptoms of heart disease.

The electronic device 104 can then receive an input indicating secondinformation related to the second field 112(2) (e.g., which, in theexample of FIG. 1, may indicate “Yes”). Based at least in part on theinput, the electronic device 104 can input the second information intothe document 106 (e.g., into the second field 112(2)). Additionally, theelectronic device 104 can send, to the remote system 102, data 110representing the second information.

The remote system 102 can receive, from the electronic device 104, thedata 110 representing the second information input into the second field112(2) (e.g., Yes). The field component 124 can then be configured toselect one or more additional fields to add to the document 106. Toselect the one or more additional fields, the field component 124 cananalyze the first information and/or the second information using therules data 136. For example, and continuing with the example above wherethe document 106 is for obtaining information associated with thepatient, a rule can indicate that at least a fourth field 112(4) isassociated with the second field 112(2) when the second informationinput into the second field 112(2) indicates “Yes”. Additionally, therule (and/or another rule) can indicate that the third field 112(3) isno longer relevant when the second information input into the secondfield 112(2) indicates “Yes”. As such, the field component 124 canselect the fourth field 112(4) for the document 106. The remote system102 can then send, to the electronic device 104, field data 134representing the fourth field 112(4). Additionally, the remote system102 can send, to the electronic device 104, additional data thatincludes a command to replace the third field 112(3) with the fourthfield 112(4).

The electronic device 104 can receive the field data 134 and/or theadditional data from the remote system 102. In the example of FIG. 1, attime T3 (e.g., the bottom-left illustration of the document 106), theelectronic device 104 can remove the third field 112(3) from thedocument 106 and then populate the document 106 with the fourth field112(4). In some examples, the fourth field 112(4) can represent aquestion related to the first information input into the first field112(1) and/or the second information input into the second field 112(2).For example, when the first information represents the initial diagnosisand the second information represents a symptom of the initialdiagnosis, the fourth field 112(4) can represent a question related toobtaining information to further determine if the symptom is in factrelated to the initial diagnosis. For examples, if the initial diagnosisincludes “Heart Disease” and the symptom includes “Chest Pains”, thenthe fourth field 112(4) can represent a question such as “Have often doyou experience chest pains?”.

The electronic device 104 can then receive an input indicating thirdinformation related to the fourth field 112(4) (e.g., “Once a day”).Based at least in part on the input, the electronic device 104 can inputthe third information into the document 106 (e.g., into the fourth field112(4)). Additionally, the electronic device 104 can send, to the remotesystem 102, data 110 representing the third information.

The remote system 102 can receive, from the electronic device 104, thedata 110 representing the third information input into the fourth field112(4) (e.g., “Once a day”). The field component 124 can then beconfigured to select one or more additional fields to add to thedocument 106. To select the one or more additional fields, the fieldcomponent 124 can analyze the first information, the second information,and/or the third information using the rules data 136. For example, andcontinuing with the example above where the document 106 is forobtaining information associated with the patient, a rule can indicatethat at least a fifth field 112(5) is associated with the fourth field112(4) when the third information input into the fourth field 112(4)indicates that the patient experiences chest pains at least four times aweek. As such, the field component 124 can select the fifth field 112(5)for the document 106. The remote system 102 can then send, to theelectronic device 104, field data 134 representing the fifth field112(5). Additionally, the remote system 102 can send, to the electronicdevice 104, additional data that includes a command to populate thedocument 106 with the fifth field 112(5).

The electronic device 104 can receive the field data 134 and/or theadditional data from the remote system 102. In the example of FIG. 1, attime T4 (e.g., the bottom-right illustration of the document 106), theelectronic device 104 can populate (e.g., add) the fifth field 112(5) tothe document 106. In some examples, the fifth field 112(5) can representa question related to the first information input into the first field112(1), the second information input into the second field 112(2),and/or the third information input into the fourth field 112(4). Forexample, when the first information represents the initial diagnosis,the second information represents a symptom of the initial diagnosis,and the third information represents how often the patient experiencesthe symptom, the fifth field 112(5) can represent a question related towhether the symptom is caused by something other than the initialdiagnosis. For examples, if the initial diagnosis includes “HeartDisease”, the symptom includes “Chest Pains”, and the frequency of thesymptom includes “Once a day”, then the fifth field 112(5) can representa question such as “How often do you eat spicy food?”.

The electronic device 104 can then receive an input indicating fourthinformation related to the fifth field 112(5) (e.g., “Twice a week”).Based at least in part on the input, the electronic device 104 can inputthe fourth information into the document 106 (e.g., into the fifth field112(5)). Additionally, the electronic device 104 can send, to the remotesystem 102, data 110 representing the fourth information.

The remote system 102 and the electronic device 104 can continue toperform similar processes until the document 106 is complete. In someexamples, to determine that the document 106 is complete, the scorecomponent 126 can be configured to determine correlation score(s) 138associated with the document 106. The score component 126 can thendetermine whether the correlation score(s) 138 satisfy (e.g., is equalto or greater than) a threshold score. Based at least in part ondetermining that the correlation score(s) 138 do not satisfy (e.g., areless than) the threshold score, the remote system 102 can continue toprovide additional fields in order to obtain additional information.Based at least in part on determining that the correlation score(s) 138satisfy the threshold score, the remote system 102 can determine thatthe document 106 is complete. The remote system 102 can then refrainfrom providing the electronic device 104 with additional fields and/orsend, to the electronic device 104, data indicating that the document106 is complete.

In some examples, such as when the document 106 is for obtaininginformation associated with the patient, a correlation score 138 canindicate a likelihood that the patient in fact has the initialdiagnosis. In some examples, the score component 126 can determine arespective correlation score 138 each time the remote system 102receives data 110 representing information input into the document 106.In some examples, the score component 126 can determine a respectivecorrelation score 138 each time the remote system 102 receives data 110representing information that is input into a threshold number of fields(e.g., one, two, five, etc.).

For example, such as at time T2, and continuing with the example abovewhere the document 106 is for obtaining information associated with thepatient, the score component 126 may have determined a first correlationscore 138 (e.g., 50) using the data 110 representing the secondinformation input into the document 106. The first correlation score 138can indicate a likelihood (e.g., 50%) that the patient has the initialdiagnosis of heart disease. The score component 126 may then havedetermined that the first correlation score 138 does not satisfy athreshold score (e.g., 90). Based at least in part on the determination,the remote system 102 may have determined to continue providing fieldsfor the document 106.

Later, such as at time T3, the score component 126 may have determined asecond correlation score 138 (e.g., 75) using the data 110 representingthe second information input into the document 106 and the data 110representing the third information input into the document 106. Thesecond correlation score 138 can indicate a likelihood (e.g., 75%) thatthe patient has the initial diagnosis of heart disease. The scorecomponent 126 may then have determined that the second correlation score138 still does not satisfy the threshold score (e.g., 90). Based atleast in part on the determination, the remote system 102 may havedetermined to continue providing fields for the document 106.

Later, such as at time T4, the score component 126 may have determined athird correlation score 138 (e.g., 95) using the data 110 representingthe second information input into the document 106, the data 110representing the third information input into the document 106, and thedata 110 representing the fourth information input into the document106. The third correlation score 138 can indicate a likelihood (e.g.,95%) that the patient has the initial diagnosis of heart disease. Thescore component 126 may then have determined that the third correlationscore 138 satisfies the threshold score (e.g., 90). Based at least inpart on the determination, the remote system 102 may have determinedthat the document 106 is complete and/or that the patient has heartdisease. The remote system 102 may then have sent, to the electronicdevice 104, data indicating that the document 106 is complete and/ordata indicating that the patient has heart disease.

Although the above example describes using a range for correlationscore(s) 138 that is between 0-100, in other examples, the scorecomponent 126 may utilize any other range. For example, the scorecomponent 126 may determine correlation score(s) that are between 0-10,where the threshold score includes a numerical value between 0-10.

Additionally, or alternatively, in some examples, the remote system 102may determine that the document 106 is complete based at least in parton the elapse of a give period of time. For example, the remote system102 can determine the period of time for obtaining information using thedocument 106. In some examples, the remote system 102 can determine theperiod of time by receiving, from the electronic device 104, data 110indicating the period of time. In some examples, the remote system 102can determine the period of time based at least in part on the type ofdocument 106. For example, if the document 106 is being utilized by anurse to obtain information from a patient, the remote system 102 candetermine that the nurse is usually provided a first period of time forobtaining the information. Additionally, if the document 106 is beingutilized by a doctor to obtain the information from the patient, theremote system 102 can determine that the doctor is usually provided asecond, different period of time for obtaining the information.

In some examples, the remote system 102 can utilize the period of timeto select one or more of the fields 112(1)-(5) for the document 106. Fora first example, if the period of time is less than a threshold periodof time (e.g., one minute, ten minutes, thirty minutes, and/or any othertime period), the field component 124 can select fields that morespecific to the initial diagnosis such that information that is morerelevant to the initial diagnosis is input into the document 106.Additionally, if the period of time is greater than the threshold periodof time, then the field component 124 can select fields that arespecific to the initial diagnosis, but also select fields that arespecific to other, possible diagnoses. By selecting such fields, theremote system 102 can determine if the initial diagnosis is correct.Additionally, if the initial diagnosis is not correct, the remote system102 can determine a new diagnosis based at least in part on theinformation input into the document 106.

For a second example, the field component 124 may utilize the period oftime to determine a number of fields to select for the document 106. Thefield component 124 can then use the number of fields when selecting thefields for the document 106. For instance, if the number of fields isless than a threshold number of fields (e.g., two fields, five fields,and/or any other number of fields), the field component 124 can selectfields that more specific to the initial diagnosis such that informationthat is more relevant to the initial diagnosis is input into thedocument 106. Additionally, if the number of fields is greater than thethreshold number of fields, then the field component 124 can selectfields that are specific to the initial diagnosis, but also selectfields that are specific to other, possible diagnoses. By selecting suchfields, the remote system 102 can determine if the initial diagnosis iscorrect. Additionally, if the initial diagnosis is not correct, theremote system 102 can determine a new diagnosis based at least in parton the information input into the document 106.

Additionally, or alternatively, in some examples, the remote system 102can determine that the document 106 is complete by receiving, from theelectronic device 104, data 110 indicating that the document 106 iscomplete.

In some examples, such as when the document is complete, the reportcomponent 128 can be configured to generate a report 140 associated withthe document 106. The report 140 can indicate one or more of the fields112(1)-(5) and/or at least a portion of the information input into thedocument 106. For example, the report 140 can indicate the fields(1)-(5) as well as the first information, the second information, thethird information, and the fourth information input into the document106. In some examples, the report 140 can further indicate thecorrelation score(s) 138 that were calculated as the document 106 wasbeing completed. The remote system 102 can then store, in the one ormore databases 130, report data 142 representing the report 140.Additionally, the remote system 102 can send, to the electronic device104 (and/or another electronic device), the report data 142 representingthe report 140.

In some examples, the remote system 102 can utilize the report data 142to determine fields for a new document. For example, if the same patientreturns for another checkup, the field component 124 can analyze thereport data 142 to determine the initial diagnosis for the patient. Thefield component 124 can then utilize the initial diagnosis to select oneor more fields for the new document. By utilizing the report data 142representing the previous report 140 to generate new documents for thepatient, the remote system 102 is able to generate documents that obtaininformation that is more specific to the patient. This information canthen be utilized to better help diagnose the patient.

As used herein, a processor, such as processor(s) 114, can includemultiple processors and/or a processor having multiple cores. Further,the processors can comprise one or more cores of different types. Forexample, the processors can include application processor units, graphicprocessing units, and so forth. In one implementation, the processor cancomprise a microcontroller and/or a microprocessor. The processor(s) 114can include a graphics processing unit (GPU), a microprocessor, adigital signal processor or other processing units or components knownin the art. Alternatively, or in addition, the functionally describedherein can be performed, at least in part, by one or more hardware logiccomponents. For example, and without limitation, illustrative types ofhardware logic components that can be used include field-programmablegate arrays (FPGAs), application-specific integrated circuits (ASICs),application-specific standard products (ASSPs), system-on-a-chip systems(SOCs), complex programmable logic devices (CPLDs), etc. Additionally,each of the processor(s) 114 can possess its own local memory, whichalso can store program components, program data, and/or one or moreoperating systems.

The memory 118 can include volatile and nonvolatile memory, removableand non-removable media implemented in any method or technology forstorage of information, such as computer-readable instructions, datastructures, program component, or other data. Such memory 118 includes,but is not limited to, RAM, ROM, EEPROM, flash memory or other memorytechnology, CD-ROM, digital versatile disks (DVD) or other opticalstorage, magnetic cassettes, magnetic tape, magnetic disk storage orother magnetic storage devices, RAID storage systems, or any othermedium which can be used to store the desired information and which canbe accessed by a computing device. The memory 118 can be implemented ascomputer-readable storage media (“CRSM”), which can be any availablephysical media accessible by the processor(s) 114 to executeinstructions stored on the memory 118. In one basic implementation, CRSMcan include random access memory (“RAM”) and Flash memory. In otherimplementations, CRSM can include, but is not limited to, read-onlymemory (“ROM”), electrically erasable programmable read-only memory(“EEPROM”), or any other tangible medium which can be used to store thedesired information and which can be accessed by the processor(s) 114.

Further, functional components can be stored in the respective memories,or the same functionality can alternatively be implemented in hardware,firmware, application specific integrated circuits, field programmablegate arrays, or as a system on a chip (SoC). In addition, while notillustrated, each respective memory, such as memory 118, discussedherein can include at least one operating system (OS) component that isconfigured to manage hardware resource devices such as the networkinterface(s), the I/O devices of the respective apparatuses, and soforth, and provide various services to applications or componentsexecuting on the processors. Such OS component can implement a variantof the FreeBSD operating system as promulgated by the FreeBSD Project;other UNIX or UNIX-like variants; a variation of the Linux operatingsystem as promulgated by Linus Torvalds; the FireOS operating systemfrom Amazon.com Inc. of Seattle, Wash., USA; the Windows operatingsystem from Microsoft Corporation of Redmond, Wash., USA; LynxOS aspromulgated by Lynx Software Technologies, Inc. of San Jose, Calif.;Operating System Embedded (Enea OSE) as promulgated by ENEA AB ofSweden; and so forth.

The network interface(s) 116 can enable communications between thecomponents and/or devices shown in environment 100 and/or with one ormore other remote systems, as well as other networked devices. Suchnetwork interface(s) 116 can include one or more network interfacecontrollers (NICs) or other types of transceiver devices to send andreceive communications over the network 108. For instance, each of thenetwork interface(s) 116 can include a personal area network (PAN)component to enable communications over one or more short-range wirelesscommunication channels. For instance, the PAN component can enablecommunications compliant with at least one of the following standardsIEEE 802.15.4 (ZigBee), IEEE 802.15.1 (Bluetooth), IEEE 802.11 (WiFi),or any other PAN communication protocol. Furthermore, each of thenetwork interface(s) 112 can include a wide area network (WAN) componentto enable communication over a wide area network.

Although the above description includes the remote system 102 generatingthe document 106, as well as performing the analysis to determinewhether the document 106 is complete, in other examples, an electronicdevice can perform some and/or all of the processes and techniquesdescribed herein for the remote system 102. For example, FIG. 2illustrates a block diagram of an example electronic device 202 that cangenerate document content by data analysis, according to variousexamples of the present disclosure. In some examples, the electronicdevice 202 can correspond to, and/or be similar to, the electronicdevice 104.

As shown, the electronic device 202 can include processor(s) 204 (whichcan correspond to, and/or be similar to, the processor(s) 114), networkinterface(s) 206 (which can correspond to, and/or be similar to, thenetwork interface(s) 116), a display 208, speaker(s) 210, microphone(s)212, input interface(s) 214 (a mouse, a trackball, a touchpad, ajoystick, a pointing stick, a stylus, etc.), and a memory 216 (which cancorrespond to, and/or be similar to, the memory 1118). In some examples,the electronic device 202 may include additional components not shown inFIG. 2. Additionally, or alternatively, in some examples, the electronicdevice 202 may not include one or more of the components shown in FIG.2.

As shown in the example of FIG. 2, the memory 216 can store data 218, adocument component 220, a rule component 222, a field component 224, ascore component 226, a report component 228, a document data 230, fielddata 232, rules data 234, correlation score(s) 236, report(s) 238,report data 240, and one or more databases 242. In some examples, thedata 218, the document component 220, the rule component 222, the fieldcomponent 224, the score component 226, the report component 228, thedocument data 230, the field data 232, the rules data 234, thecorrelation score(s) 236, the report(s) 238, the report data 240, andthe one or more databases 242 can correspond respectively to, and/or berespectively similar to, the data 110, the document component 120, therules component 122, the field component 124, the score component 126,the report component 128, the document data 132, the field data 134, therules data 136, the correlation score(s) 138, the report(s) 140, thereport data 142, and the one or more databases 130.

As discussed above, in some examples, the electronic device 202 canperform some and/or all of the processes of the remote system 102. Forexample, the electronic device 202 can utilize the document component220 to select and/or provide (e.g., display) a document. The electronicdevice 202 can then utilize the field component 224 to select one ormore fields for the document, using the processes described above.Furthermore, the electronic device 202 can utilize the score component226 to calculate correlation score(s) 236 for the document, and thendetermine whether the correlation score(s) 236 satisfy a thresholdscore, using the processes described above. Moreover, the electronicdevice 202 can utilize the report component 228 to generate a report 238for the document, using the processes described above.

While these are just a few examples of processes that can be performedby the electronic device 202, in some examples, the electronic device202 can be capable of performing all of the processes described abovewith regard to the remote system 102. Additionally, in some examples,the remote system 102 can perform at least a first portion of theprocesses described above and the electronic device 202 can perform atleast a second portion of the processes.

FIG. 3 illustrates a diagram of a first example of updating a document302 with fields as information is being input into the document 302,according to various examples of the present disclosure. For example,over a period of time 304, the document 302 can be populated with fields306(1)-(4) as information 308(1)-(4) is input into the document 302. Forinstance, at time 304 T1, the document 302 includes a first field306(1). While displaying the first field 306(1), input representingfirst information 308(1) related to the first field 306(1) can be inputinto the document 302.

Based at least in part on the first information 308(1), the remotesystem 102 (and/or the electronic device 202) can select a second field306(2) for the document 302. A such, at time 304 T2, the document 302can be populated with the second field 306(2). While displaying thesecond field 306(2), input representing second information 308(2)related to the second field 306(2) can be input into the document 302.

Based at least in part on the first information 308(1) and/or the secondinformation 308(2), the remote system 102 (and/or the electronic device202) can select a third field 306(3) for the document 302. As such, attime 304 T3, the document 302 can be populated with the third field306(3). While displaying the third field 306(3), input representingthird information 308(3) related to the third field 306(3) can be inputinto the document 302.

Finally, based at least in part on the first information 308(1), thesecond information 308(2), and/or the third information 308(3), theremote system 102 (and/or the electronic device 202) can select a fourthfield 306(4) for the document 302. As such, at time 304 T4, the document302 can be populated with the fourth field 306(4). While displaying thefourth field 306(4), input representing fourth information 308(4)related to the fourth field 306(4) can be input into the document 302.

FIG. 4 illustrates a diagram of a second example of updating a document402 with fields as information is being input into the document 402,according to various examples of the present disclosure. For example,over a period of time 404, the document 402 can be populated with fields406(1)-(4) as information 408(1)-(3) is input into the document 402. Forinstance, at time 404 T1, the document 402 includes a first field406(1). While displaying the first field 406(1), input representingfirst information 408(1) related to the first field 406(1) can be inputinto the document 402.

Based at least in part on the first information 408(1), the remotesystem 102 (and/or the electronic device 202) can determine a firstcorrelation score associated with the document 402. In the example ofFIG. 4, the remote system 102 (and/or the electronic device 202) candetermine that the first correlation score does not satisfy a thresholdscore. As such, the remote system 102 (and/or the electronic device 202)can select a second field 406(2) for the document 402. As such, at time404 T2, the document 402 can be populated with the second field 406(2).While displaying the second field 406(2), input representing secondinformation 408(2) related to the second field 406(2) can be input intothe document 402.

Based at least in part on the first information 408(1) and/or the secondinformation 408(2), the remote system 102 (and/or the electronic device202) can determine a second correlation score associated with thedocument 402. In the example of FIG. 4, the remote system 102 (and/orthe electronic device 202) can determine that the second correlationscore does not satisfy the threshold score. As such, the remote system102 (and/or the electronic device 202) can select a third field 406(3)and a fourth field 406(4) for the document 402. As such, at time 404 T3,the document 402 can be populated with the third field 406(3) and thefourth field 406(4). While displaying the third field 406(3) and thefourth field 406(4), input representing third information 408(3) relatedto the third field 406(3) can be input into the document 402.

Finally, based at least in part on the first information 408(1), thesecond information 408(2), and/or the third information 408(3), theremote system 102 (and/or the electronic device 202) can determine athird correlation score associated with the document 402. In the exampleof FIG. 4, the remote system 102 (and/or the electronic device 202) canthen determine that the third correlation score satisfies the thresholdscore. As such, the remote system 102 (and/or the electronic device 202)can determine that the document 402 is complete and/or informationrelated to the fourth field 406(4) is no longer necessary. As such, attime 404 T4, the fourth field 406(4) can be removed from the document402. Additionally, the document 402 can be populated with an indicationthat the document 402 is complete 410.

FIG. 5 illustrates a diagram of a third example of updating a document502 with fields as information is being input into the document 502,according to various examples of the present disclosure. For example,over a period of time 504, the document 502 can be populated with fields506(1)-(5) as information 508(1)-(4) is input into the document 502. Forinstance, at time 504 T1, the document 502 includes a first field506(1). In the example of FIG. 5, the first field 506(1) can correspondto a question asking for an initial diagnosis. While displaying thefirst field 506(1), input representing first information 508(1) relatedto the first field 506(1) can be input into the document 502. Forexample, the first information 508(1) can be related to the initialdiagnosis.

Based at least in part on the first information 508(1), the remotesystem 102 (and/or the electronic device 202) can determine a firstcorrelation score associated with the document 502, where the firstcorrelation score indicates a likelihood that a patient has the initialdiagnosis. In the example of FIG. 5, the remote system 102 (and/or theelectronic device 202) can determine that the first correlation scoredoes not satisfy a threshold score. As such, the remote system 102(and/or the electronic device 202) can select a second field 506(2) forthe document 502. As such, at time 504 T2, the document 502 can bepopulated with the second field 506(2). While displaying the secondfield 506(2), input representing second information 508(2) related tothe second field 506(2) can be input into the document 502.

Based at least in part on the first information 508(1) and/or the secondinformation 508(2), the remote system 102 (and/or the electronic device202) can determine a second correlation score associated with thedocument 502, where the second correlation score indicates a likelihoodthat the patient has the initial diagnosis. In the example of FIG. 5,the remote system 102 (and/or the electronic device 202) can determinethat the second correlation score does not satisfy the threshold score.As such, the remote system 102 (and/or the electronic device 202) canselect a third field 506(3) for the document 502. As such, at time 504T3, the document 502 can be populated with the third field 506(3). Whiledisplaying the third field 506(3), input representing third information508(3) related to the third field 506(3) can be input into the document502.

Finally, based at least in part on the first information 508(1), thesecond information 508(2), and/or the third information 508(3), theremote system 102 (and/or the electronic device 202) can determine athird correlation score associated with the document 502, where thethird correlation score indicates a likelihood that the patient has theinitial diagnosis. In the example of FIG. 5, the remote system 102(and/or the electronic device 202) can then determine that the thirdcorrelation score still does not satisfy the threshold score.Additionally, the remote system 102 (and/or the electronic device 202)can determine a fourth correlation score based at least in part on thefirst information 508(1), the second information 508(2), and/or thethird information 508(3). The fourth correlation score can indicate alikelihood that the patient has a new diagnosis. The remote system 102(and/or the electronic device 202) can then determine that the fourthcorrelation score satisfies a threshold score and/or that the fourthcorrelation score is greater than the third correlation score. Based atleast in part on the determination(s), the remote system 102 (and/or theelectronic device 202) can determine that the patient has the newdiagnosis.

As such, the remote system 102 (and/or the electronic device 202) canselect at least a fourth field 506(4) that includes fourth information508(4) representing the new diagnosis. The remote system 102 (and/or theelectronic device 202) can also select a fifth field 506(5) associatedwith the new diagnosis. As such, at time 504 T4, the document 502 can bepopulated with the fourth field 506(4), the fourth information 508(4),and the fifth field 506(5).

FIG. 6 illustrates a diagram of an example structure 600 that can beutilized to select fields for a document, according to various examplesof the present disclosure. As shown, the structure 600 includes a firstfield 602 located at a first level (and/or first step) of the structure600. A first rule associated with the structure 600 can indicate that iffirst information 604 is input into the first field 602, then a secondfield 606 is selected for the document. The first rule can furtherindicate that if second information 608 is input into the first field602, then a third field 610 is selected for the document. The secondfield 606 and the third field 610 are located at a second level (and/orsecond step) of the structure 600.

Additionally, a second rule associated with the structure 600 canindicate that if third information 612 is input into the second field606, then a fourth field 614 is selected for the document. The secondrule can further indicate that if fourth information 616 is input intothe third field 606, then a fifth field 618 is selected for thedocument. Furthermore, a third rule associated with the structure 600can indicate that if fifth information 620 is input into the third field610, then a sixth field 622 is selected for the document. The third rulecan further indicate that if sixth information 624 is input into thethird field 610, then a seventh field 626 is selected for the document.The fourth field 614, the fifth field 618, the sixth field 622, and theseventh field 626 are located in a third level (and/or third step) ofthe structure 600.

As shown in the example of FIG. 6, the structure 600 can continue suchthat new fields are selected when information is input a previous fieldin the structure 600. In some examples, although no illustrated in FIG.6, the structure 600 can further be connected to another structure. Forexample, if the structure 600 is associated with a first diagnosis, andbased at least in part on the information input into the document theremote system 102 (and/or the electronic device 202) identifies a seconddiagnosis, then the remote system (and/or the electronic device 202) canselect a second structure associated with the second diagnosis.

Each of the processes described herein, including the processes 700,800, 900, 1000, and 1100, are illustrated as a collection of blocks in alogical flow graph, which represent a sequence of operations that can beimplemented in hardware, software, or a combination thereof. In thecontext of software, the blocks represent computer-executableinstructions stored on one or more computer-readable storage media that,when executed by one or more processors, perform the recited operations.Generally, computer-executable instructions include routines, programs,objects, components, data structures, and the like that performparticular functions or implement particular abstract data types. Theorder in which the operations are described is not intended to beconstrued as a limitation, and any number of the described blocks can becombined in any order and/or in parallel to implement the processes.Additionally, any number of the described blocks can be optional andeliminated to implement the processes.

FIGS. 7A-7B illustrate a flow diagram of an example process 700 forupdating fields of a document as information is being input into thedocument, according to various examples of the present disclosure. Eventhough the example process 700 of FIGS. 7A-7B is described as beingperformed by the remote system 102, in other examples, at least some ofthe example process 700 of FIGS. 7A-7B can be performed by one or moreother electronic devices. For example, at least some of the exampleprocess 700 of FIGS. 7A-7B can be performed by the electronic device 104and/or the electronic device 202.

At block 702, the process 700 includes storing first data representing afirst document associated with a first type of user. For example, theremote system 102 can store the first data representing the firstdocument associated with the first type of user. In some examples, thefirst data can further represent an identifier associated with the firsttype of user. In some examples, types of user can include, but are notlimited to, doctors, nurses, managers, associates, employees, and/or anyother type of position within a group, business, corporation, medicalfacility, and/or so forth.

At block 704, the process 700 includes storing second data representinga second document associated with a second type of user. For example,the remote system 102 can store the second data representing the seconddocument associated with the second type of user. In some examples, thesecond data can further represent an identifier associated with thesecond type of user.

At 706, the process 700 includes receiving third data representing thefirst type of user. For example, the remote system 102 can receive, froman electronic device, the third data representing the first type ofuser. In some examples, the third data can represent an identifierassociated with the first type of user. In some examples, the third datacan further represent a request for the first document.

At 708, the process 700 includes selecting the first document based atleast in part on the third data. For example, the remote system 102 canselect the first document based at least in part on the third datarepresenting the first type of user. In some examples, to select thefirst document, the remote system 102 can match the identifierrepresented by the third data to the identifier represented by the firstdata. Based at least in part on the match, the remote system 102 canselect the first document.

At 710, the process 700 includes sending the first data representing thefirst document. For example, the remote system 102 can send, to theelectronic device, the first data representing the first document. Insome examples, the sending of the first data can cause the electronicdevice to display the first document. In some examples, the firstdocument can include one or more initial fields. For example, if thefirst document is associated with obtaining information associated witha patient, the one or more initial fields can include a field forinputting an initial diagnosis associated with the patient.

At 712, the process 700 includes determining a type of diagnosis. Forexample, the remote system 102 can determine the type of diagnosis. Insome examples, the remote system 102 can determine the type of diagnosisbased at least in part on receiving, from the electronic device, datarepresenting the type of diagnosis. In some examples, the remote system102 can determine the type of diagnosis by analyzing one or more reportspreviously generated for the patient. For example, the one or morereports can indicate that the patient has the type of diagnosis.

At 714, the process 700 includes selecting at least a first field basedat least in part on the type of diagnosis. For example, the remotesystem 102 can select the at least the first field based at least inpart on the type of diagnosis. In some examples, the at least the firstfield can correspond to one or more questions associated with the typeof diagnosis. For example, the one or more questions can be asking forinformation related to one or more symptoms associated with the type ofdiagnosis.

At 716, the process 700 includes sending fourth data representing thefirst field and a command to populate the first document with the firstfield. For example, the remote system 102 can send, to the electronicdevice, the fourth data representing the first field and the command topopulate the first document with the first field. In some examples, thefourth data can cause the electronic device to display the first fieldas part of the first document.

At 718, the process 700 includes receiving fifth data representing firstinformation related to the first field. For example, the remote system102 can receive, from the electronic device, the fifth data representingthe first information related to the first field. In some examples,based at least in part on receiving the fifth data, the remote system102 can determine a first correlation score associated with the firstinformation. The remote system 102 can then determine whether the firstcorrelation score satisfies a threshold score.

At 720, the process 700 includes selecting at least a second field basedat least in part on the first information. For example, the remotesystem 102 can select the at least the second field based at least inpart on the first information. In some examples, the at least the secondfield can correspond to one or more questions associated with the typeof diagnosis. For example, the one or more questions can be asking forfurther information related to the one or more symptoms associated withthe type of diagnosis. In some examples, the at least the second fieldcan further correspond to one or more questions associated with thefirst information. For example, the one or more questions can be askingfor further information that clarifies the first information.

At 722, the process 700 includes sending sixth data representing thesecond field and a command to populate the first document with thesecond field. For example, the remote system 102 can send, to theelectronic device, the sixth data representing the second field and thecommand to populate the first document with the second field. In someexamples, the sixth data can cause the electronic device to display thesecond field as part of the first document.

At 724, the process 700 includes receiving seventh data representingsecond information related to the second field. For example, the remotesystem 102 can receive, from the electronic device, the seventh datarepresenting the second information related to the second first field.In some examples, based at least in part on receiving the seventh data,the remote system 102 can determine a second correlation scoreassociated with the first information and/or the second information. Theremote system 102 can then determine whether the second correlationscore satisfies the threshold score.

At 726, the process 700 includes generating a report associated with thefirst document. For example, the remote system 102 can generate thereport associated with the first document. In some examples, the reportcan indicate at least the first field, the first information, the secondfield, and the second information. The remote system 102 can then storedata representing the report in one or more databases.

FIG. 8 illustrates a flow diagram of an example process 800 for updatingfields of a document, according to various examples of the presentdisclosure. Even though the example process 800 of FIG. 8 is describedas being performed by the remote system 102, in other examples, at leastsome of the example process 800 of FIG. 8 can be performed by one ormore other electronic devices. For example, at least some of the exampleprocess 800 of FIG. 8 can be performed by the electronic device 104and/or the electronic device 202.

At 802, the process 800 includes providing a document. For example, theremote system 102 can send, to an electronic device, data representingthe document. In some examples, the remote system 102 provides thedocument based at least in part on receiving, from the electronicdevice, data representing a request for the document. In some examples,the document is associated with a type of user that is using theelectronic device.

At 804, the process 800 includes selecting, using information associatedwith the document, a field to be input into the document. For example,the remote system 102 can select the field using information that isincluded within the document. In some examples, the information canindicate a diagnosis of a patient. In some examples, the information canbe related to one or more other fields included within the document.

At 806, the process 800 includes providing the field. For example, theremote system 102 can send, to the electronic device, data representingthe field. In some examples, the data can further include a command toinput the field into the document. In some examples, the data causes theelectronic device to input the field into the document.

At 808, the process 800 includes receiving data representing additionalinformation associated with the field. For example, the remote system102 can receive, from the electronic device, the data representing theadditional information associated with the field. In some examples, theremote system 102 can then store the data within one or more databases.

At 810, the process 800 includes determining whether to provide anadditional field. For example, the remote system 102 can determinewhether to provide an additional field for the document. In someexamples, to make the determination, the remote system 102 can analyzethe information and, based at least in part on the analysis, determine acorrelation score. The remote system 102 can then determine not toprovide the additional field when the correlation score satisfies athreshold score, but determine to provide the additional field when thecorrelation score does not satisfy the threshold score. In someexamples, to make the determination, the remote system 102 can determinewhether a period of time has elapsed. The remote system 102 can thendetermine not to provide the additional field when the period of timehas elapsed, but determine to provide the additional field when theperiod of time has not yet elapsed. Still, in some examples, the remotesystem 102 can determine not to provide the additional field based atleast in part on receiving, from the electronic device, data indicatingthat the document is complete.

If at 810 it is determined to provide the additional field, then theprocess 800 can repeat back at 804. However, if at 810 it is determinedto not provide the additional field, then at 812, the process 800includes determining that the document is complete. For example, theremote system 102 can determine that the document is complete. In someexamples, the remote system 102 can then generate a report associatedwith the document.

FIG. 9 illustrates a flow diagram of an example process 800 for usingscores to determine whether a document is complete, according to variousexamples of the present disclosure. Even though the example process 900of FIG. 9 is described as being performed by the remote system 102, inother examples, at least some of the example process 900 of FIG. 9 canbe performed by one or more other electronic devices. For example, atleast some of the example process 900 of FIG. 9 can be performed by theelectronic device 104 and/or the electronic device 202.

At 902, the process 900 includes providing a document that includes atleast a first field. For example, the remote system 102 can send, to anelectronic device, data representing the document that includes thefirst field. In some examples, the remote system 102 provides thedocument based at least in part on receiving, from the electronicdevice, data representing a request for the document. In some examples,the document is associated with a type of user that is using theelectronic device.

At 904, the process 900 includes receiving a first indicationrepresenting first information associated with the first field. Forexample, the remote system 102 can receive, from the electronic device,data indicating the first information associated with the first field.In some examples, if the first field includes a first question, thefirst information can correspond to a response to the first question.

At 906, the process 900 includes determining a score based at least inpart on the first information. For example, the remote system 102 candetermine the score based at least in part on the first information. Insome examples, if the document is associated with diagnosing a patient,the score can indicate a likelihood that an initial diagnosis for thepatient is correct (e.g., the patient has the disease). In suchexamples, the score can be greater when the first information indicatesthat the patient is experience one or more symptoms associated with thedisease, but be lower when the first information indicates that thepatient is not experiencing one or more symptoms associated with thedisease.

At 908, the process 900 includes determining that the score does notsatisfy a threshold score. For example, the remote system 102 candetermine that the score does not satisfy the threshold score. In someexamples, based at least in part on the determination, the remote system102 can determine to provide additional fields for the document.

At 910, the process 900 includes determining a second field associatedwith the document. For example, the remote system 102 can determine thesecond field associated with the document. In some examples, the remotesystem 102 determines the second field using the first information. Forexample, the second field can correspond to a second question related tothe first information. For instance, the second question can inquireabout more details to the first information.

At 912, the process 900 includes providing the second field. Forexample, the remote system 102 can send, to the electronic device, datarepresenting the second field. In some examples, the data can furtherrepresent a command to populate the document with the second field.

At 914, the process 900 includes receiving a second indicationrepresenting second information associated with the second field. Forexample, the remote system 102 can receive, from the electronic device,data indicating the second information associated with the second field.In some examples, if the second field includes the second question, thesecond information can correspond to a response to the second question.In some examples, the remote system 102 can then determine an additionalscore using the first information and/or the second information. In suchexamples, if the additional score satisfies the threshold score, thenthe remote system 102 can determine that the document is complete.However, if the additional score does not satisfy the threshold score,then the remote system 102 can continue to provide additional fields tobe added to the document.

FIG. 10 illustrates a flow diagram of an example process 1000 for usinga period of time to select at least one field for a document, accordingto various examples of the present disclosure. Even though the exampleprocess 1000 of FIG. 10 is described as being performed by the remotesystem 102, in other examples, at least some of the example process 1000of FIG. 10 can be performed by one or more other electronic devices. Forexample, at least some of the example process 1000 of FIG. 10 can beperformed by the electronic device 104 and/or the electronic device 202.

At 1002, the process 1000 includes receiving a first indication of aperiod of time. For example, the remote system 102 can receive the firstindication of the period of time. In some examples, to receive the firstindication, the remote system 102 can receive, from an electronicdevice, data representing the period of time. In some examples, toreceive the first indication, the remote system 102 can receive dataindicating a document type associated with the document. The remotesystem 102 can then determine the period of time based at least in parton the document type.

At 1004, the process 1000 includes providing a document that includes atleast a first field. For example, the remote system 102 can send, to theelectronic device, data representing the document that includes thefirst field. In some examples, the remote system 102 provides thedocument based at least in part on receiving, from the electronicdevice, data representing a request for the document. In some examples,the document is associated with a type of user that is using theelectronic device.

At 1006, the process 1000 includes receiving a second indicationrepresenting first information associated with the first field. Forexample, the remote system 102 can receive, from the electronic device,data indicating the first information associated with the first field.In some examples, if the first field includes a first question, thefirst information can correspond to a response to the first question.

At 1008, the process 1000 includes determining a second field based atleast in part on the period of time. For example, the remote system 102can determine the second field based at least in part on the period oftime. In some examples, the remote system 102 can further determine thesecond field based at least in part on the first information.

At 1010, the process 1000 includes providing the second field. Forexample, the remote system 102 can send, to the electronic device, datarepresenting the second field. In some examples, the data can furtherrepresent a command to populate the document with the second field.

At 1014, the process 1000 includes receiving a third indicationrepresenting second information associated with the second field. Forexample, the remote system 102 can receive, from the electronic device,data indicating the second information associated with the second field.In some examples, if the second field includes the second question, thesecond information can correspond to a response to the second question.

FIG. 11 illustrates a flow diagram of an example process 1100 for anelectronic device updating fields of a document, according to variousexamples of the present disclosure. At 1102, the process 1100 includesproviding a document. For example, the electronic device can display thedocument. In some examples, before displaying the document, theelectronic device can receive, from the remote system 102, datarepresenting the document. In some examples, the electronic deviceprovides the document based at least in part on receiving an inputassociated with providing the document.

At 1104, the process 1100 includes providing a field associated with thedocument. For example, the electronic device can display the fieldassociated with the document. In some examples, the electronic devicedisplays the field after selecting the field for the document. In someexamples, the electronic device displays the field after receiving, fromthe remote system 102, data representing the field.

At 1106, the process 1100 includes receiving an indication representinginformation related to the field. For example, the electronic device canreceive an input indicating the information related to the field. Insome examples, based at least in part on the input, the electronicdevice can add the information to the document. In some examples, basedat least in part on the input, the electronic device can send, to theremote system 102, data representing the information.

At 1108, the process 1100 includes determining whether to provide anadditional field. For example, the electronic device can determinewhether to provide an additional field for the document. In someexamples, to make the determination, the electronic device can analyzethe information and, based at least in part on the analysis, determine acorrelation score. The electronic device can then determine not toprovide the additional field when the correlation score satisfies athreshold score, but determine to provide the additional field when thecorrelation score does not satisfy the threshold score. In someexamples, to make the determination, the electronic device can determinewhether a period of time has elapsed. The electronic device can thendetermine not to provide the additional field when the period of timehas elapsed, but determine to provide the additional field when theperiod of time has not yet elapsed.

In some examples, to make the determination, the electronic device candetermine whether an input was received indicating that the document iscomplete. The electronic device can then determine not to provide theadditional field when the input is received, but determine to providethe additional field when the input has yet to be received. Still, insome examples, to make the determination, the electronic device candetermine whether the electronic device has received, from the remotesystem 102, data representing the additional field. The electronicdevice can then determine not to provide the additional field when thedata has not been received, but determine to provide the additionalfield when the data has been received.

If at 1108 it is determined to provide the additional field, then theprocess 1100 can repeat back at 1104. However, if at 1108 it isdetermined to not provide the additional field, then at 1110, theprocess 1100 includes determining that the document is complete. Forexample, if the electronic device determines not to provide theadditional field, then the electronic device can determine that thedocument is complete.

While the foregoing invention is described with respect to the specificexamples, it is to be understood that the scope of the invention is notlimited to these specific examples. Since other modifications andchanges varied to fit particular operating requirements and environmentswill be apparent to those skilled in the art, the invention is notconsidered limited to the example chosen for purposes of disclosure, andcovers all changes and modifications which do not constitute departuresfrom the true spirit and scope of this invention.

Although the application describes embodiments having specificstructural features and/or methodological acts, it is to be understoodthat the claims are not necessarily limited to the specific features oracts described. Rather, the specific features and acts are merelyillustrative some embodiments that fall within the scope of the claimsof the application.

What is claimed is:
 1. A system comprising: one or more processors; andone or more computer-readable media storing instructions that, whenexecuted by the one or more processors, cause the one or more processorsto perform operations comprising: storing a first document that isassociated with a first type of user and a first plurality of questions;storing a second document that is associated with a second type of userand a second plurality of questions; receiving, from an electronicdevice, an indication of the first type of user; based at least in parton the indication, selecting the first document; sending the firstdocument to the electronic device; determining a type of diagnosisassociated with a patient; based at least in part on the type ofdiagnosis, selecting at least a first question from the first pluralityof questions, the first question associated with requesting firstsymptom information from the patient that is related to the type ofdiagnosis; sending, to the electronic device, the first question and afirst command to cause the electronic device to populate the firstdocument with the first question; receiving, from the electronic device,the first symptom information related to the first question;determining, based at least in part on the first symptom information, aconfidence score representing a probability that the first symptominformation is indicative of the type of diagnosis associated with thepatient; based at least in part on the confidence score not satisfying athreshold score, selecting at least a second question from the firstplurality of questions, the second question associated with requestingsecond symptom information from the patient that is related to the typeof diagnosis; sending, to the electronic device, the second question anda second command to cause the electronic device to populate the firstdocument with the second question; receiving, from the electronicdevice, the second symptom information related to the second question;and generating a report that indicates at least the first symptominformation related to the first question and the second symptominformation related to the second question.
 2. The system as recited inclaim 1, the one or more computer-readable media storing furtherinstructions that, when executed by the one or more processors, causethe one or more processors to perform operations comprising: storing afirst rule, the first rule associating the first symptom informationrelated to the first question with the second question; and storing asecond rule, the second rule associating third symptom informationrelated to the first question with a third question, wherein theselecting of the second question is further based at least in part onthe first rule.
 3. The system as recited in claim 1, wherein theconfidence score is a first confidence score, the one or morecomputer-readable media storing further instructions that, when executedby the one or more processors, cause the one or more processors toperform operations comprising: determining, based at least in part on atleast one of the first symptom information or the second symptominformation, a second confidence score associated with the type ofdiagnosis; determining that the second confidence score satisfies thethreshold score; and based at least in part on the second confidencescore satisfying the threshold score, determining that the document iscomplete.
 4. The system as recited in claim 1, wherein the report is afirst report, and wherein the one or more computer-readable media storefurther instructions that, when executed by the one or more processors,cause the one or more processors to perform operations comprising:storing a second report associated with a first patient; storing a thirdreport associated with a second patient, the third report indicating thetype of diagnosis; analyzing the second report with respect to the thirdreport; and based at least in part on the analyzing, identifying asimilarity between the second report and the third report, wherein thedetermining the type of diagnosis is based at least in part on thesimilarity between the second report and the third report.
 5. A methodcomprising: providing, by one or more computing devices and to anelectronic device, a document that includes at least a first field thatis associated with requesting first information related to determining atype of diagnosis associated with a patient; receiving, by the one ormore computing devices and from the electronic device, the firstinformation associated with the first field; determining, by the one ormore computing devices and based at least in part on the firstinformation, a score representing a probability that the firstinformation is indicative of the type of diagnosis associated with thepatient; determining, by the one or more computing devices, that thescore does not satisfy a threshold score; based at least in part on thescore not satisfying the threshold score, determining, by the one ormore computing devices, a second field that is associated withrequesting second information related to determining the type ofdiagnosis associated with the patient; sending, by the one or morecomputing devices and to the electronic device, the second field and acommand to cause the electronic device to populate the document with thesecond field; and receiving, by the one or more computing devices andfrom the electronic device, the second information associated with thesecond field.
 6. The method as recited in claim 5, further comprising:determining, by the one or more computing devices, an additional scorebased at least in part on at least one of the first information or thesecond information; determining, by the one or more computing devices,that the additional score satisfies the threshold score; and based atleast in part on the additional score satisfying the threshold score,refraining from providing, by the one or more computing devices, a thirdfield.
 7. The method as recited in claim 5, further comprising:determining, by the one or more computing devices, an additional scorebased at least in part on at least one of the first information or thesecond information; determining, by the one or more computing devices,that the additional score satisfies the threshold score; anddetermining, by the one or more computing devices, the type of diagnosisbased at least in part on the additional score satisfying the thresholdscore.
 8. The method as recited in claim 5, further comprising:receiving, by the one or more computing devices, an indication of aperiod of time, wherein the determining of the second field is furtherbased at least in part on the period of time.
 9. The method as recitedin claim 5, further comprising: receiving, by the one or more computingdevices, an indication representing a type of user; and selecting, bythe one or more computing devices, the document from a plurality ofdocuments, wherein the document is related to the type of user.
 10. Themethod as recited in claim 5, wherein the document is associated with afirst checkup, and wherein the method further comprises: storing, by theone or more computing devices,-a report that is associated with a secondcheckup; identifying, by the one or more computing devices, thirdinformation represented by the report; and determining, by the one ormore computing devices, the first field based at least in part on thethird information.
 11. The method as recited in claim 5, wherein thetype of diagnosis comprises a first type of diagnosis, and wherein themethod further comprises: receiving, by the one or more computingdevices, an indication of a second type of diagnosis; determining, bythe one or more computing devices, at least a third field that isassociated with the second type of diagnosis; and providing, by the oneor more computing devices, the third field.
 12. The method as recited inclaim 5, further comprising: storing, by the one or more computingdevices, a first rule, the first rule associating the first informationwith the second field; and storing, by the one or more computingdevices, a second rule, the second rule associating third informationwith a third field, wherein the determining of the second fieldassociated with the document is further based at least in part on thefirst rule.
 13. The method as recited in claim 5, wherein: the documentfurther includes a third field; and the sending of the second field andthe command to cause the electronic device to populate the document withthe second field comprises sending, by the one or more computingdevices, the second field and the command instead of the third field.14. The method as recited in claim 5, further comprising generating, bythe one or more computing devices, a report that includes at least: thefirst field; the first information input into the first field; thesecond field; and the second information input into the second field.15. A method comprising: providing, at a first instance of time and byone or more computing devices, a document that includes at least a firstfield comprising a first question, the first question associated withrequesting first information related to a type of diagnosis associatedwith a user; receiving, by the one or more computing devices, the firstinformation; providing, at a second instance of time and by the one ormore computing devices, the document; determining, by the one or morecomputing devices, a period of time between the first instance of timeand the second instance of time; based at least in part on the period oftime meeting or exceeding a threshold period of time, altering thedocument such that the first field of the document comprises a secondquestion instead of the first question, the second question associatedwith requesting second information related to the type of diagnosis; andproviding, by the one or more computing devices, the document includingat least the first field comprising the second question.
 16. The methodas recited in claim 15, further comprising: determining, by the one ormore computing devices, a score based at least in part on at least oneof the first information or the second information; determining, by theone or more computing devices, that the score satisfies a thresholdscore; and determining, by the one or more computing devices, that thedocument is complete based at least in part on the score satisfying thethreshold score.
 17. The method as recited in claim 15, furthercomprising: storing, by the one or more computing devices, first dataassociating the first field comprising the first question with the firstinstance of time; and storing, by the one or more computing devices,second data associating the first field comprising the second questionwith the second instance of time.
 18. The method as recited in claim 15,wherein the document is a first document, and wherein the method furthercomprises: storing, by the one or more computing devices, first dataassociating the first document with a first type of user; storing, bythe one or more computing device, second data associating a seconddocument with a second type of user; receiving, by the one or morecomputing devices, an indication that the first type of user isrequesting the first document; and selecting, by the one or morecomputing devices, the first document based at least in part on theindication.
 19. The system as recited in claim 1, wherein the sendingthe first document comprises sending the first document to theelectronic device at a first instance of time, the one or morecomputer-readable media storing further instructions that, when executedby the one or more processors, cause the one or more processors toperform operations comprising: sending the first document to theelectronic device at a second instance of time; determining, by the oneor more computing devices, a period of time between the first instanceof time and the second instance of time; based at least in part on theperiod of time, altering the first document such that at least the firstquestion of the first document comprises a different context that isassociated with requesting third symptom information related to the typeof diagnosis; and providing, by the one or more computing devices, thefirst document including at least the first question comprising thedifferent context.
 20. The method as recited in claim 5, wherein theproviding the document comprises providing the document to theelectronic device at a first instance of time, the method furthercomprising: receiving, at a second instance of time and from theelectronic device, a request to provide the document; determining, bythe one or more computing devices, a period of time between the firstinstance of time and the second instance of time; based at least in parton the period of time, altering the document such that at least thefirst field of the document comprises a different context that isassociated with requesting third information related to determining thetype of diagnosis; and providing, by the one or more computing devices,the document including at least the first field comprising the differentcontext.